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99 lines
4.0 KiB
99 lines
4.0 KiB
import configparser |
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import cv2 |
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import os |
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import time |
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from discord_webhook import DiscordWebhook, DiscordEmbed |
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import logging |
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from datetime import datetime |
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from pycoral.adapters.common import input_size |
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from pycoral.adapters.detect import get_objects |
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from pycoral.utils.dataset import read_label_file |
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from pycoral.utils.edgetpu import make_interpreter |
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from pycoral.utils.edgetpu import run_inference |
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def main(): |
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last_time = datetime.now() |
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time.sleep(5) |
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webhook = DiscordWebhook(url=config["DEFAULT"]["url"]) |
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labels=config["DEFAULT"]["default_labels"] |
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model=config["DEFAULT"]["default_model"] |
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threshold=float(config["DEFAULT"]["default_threshold"]) |
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top_k= int(config["DEFAULT"]["top_K"]) |
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grace_time= int(config["DEFAULT"]["grace_time"]) |
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stream=config["DEFAULT"]["default_stream"] |
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dump_path=config["DEFAULT"]["dump_path"] |
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logging.warning('Loading {} with {} labels.'.format(model, labels)) |
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interpreter = make_interpreter(model) |
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interpreter.allocate_tensors() |
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labels = read_label_file(labels) |
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inference_size = input_size(interpreter) |
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cap = cv2.VideoCapture(stream) |
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while cap.isOpened(): |
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ret, frame = cap.read() |
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if not ret: |
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break |
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cv2_im = frame |
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cv2_im_rgb = cv2.cvtColor(cv2_im, cv2.COLOR_BGR2RGB) |
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cv2_im_rgb = cv2.resize(cv2_im_rgb, inference_size) |
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run_inference(interpreter, cv2_im_rgb.tobytes()) |
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objs = get_objects(interpreter,threshold)[:top_k] |
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cv2_im,alarm,message = detect_and_alarm(cv2_im, inference_size, objs, labels,threshold) |
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#print(alarm,message) |
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if alarm and is_time(last_time,grace_time): |
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last_time=datetime.now() |
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logging.warning("people alarm",last_time) |
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#im_resize = cv2.resize(cv2_im, (640, 480)) |
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is_success, im_buf_arr = cv2.imencode(".jpg", cv2_im) |
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byte_im = im_buf_arr.tobytes() |
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webhook.add_file(file=byte_im,filename='capture.png') |
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embed = DiscordEmbed(title='Detected', description=message, color='ff2345') |
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embed.set_image(url='attachment://capture.png') |
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webhook.add_embed(embed) |
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response = webhook.execute(remove_embeds=True) |
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logging.debug(response) |
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if config["DEFAULT"]["DUMP_VIDEO"]=="True": |
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os.system(f"ffmpeg -i {stream} -acodec copy -vcodec copy -t {grace_time} {dump_path}record_{last_time.strftime('%d-%m-%Y_%H-%M-%S')}.mp4 ") |
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if config["DEFAULT"]["CV_DEBUG"]=="True": |
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cv2.imshow('frame', cv2_im) |
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if cv2.waitKey(1) & 0xFF == ord('q'): |
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break |
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cap.release() |
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cv2.destroyAllWindows() |
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def detect_and_alarm (cv2_im, inference_size, objs, labels,threshold): |
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height, width, channels = cv2_im.shape |
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scale_x, scale_y = width / inference_size[0], height / inference_size[1] |
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for obj in objs: |
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if obj.id == 0 and obj.score>threshold*1.09: |
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bbox = obj.bbox.scale(scale_x, scale_y) |
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x0, y0 = int(bbox.xmin), int(bbox.ymin) |
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x1, y1 = int(bbox.xmax), int(bbox.ymax) |
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percent = int(100 * obj.score) |
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label = '{}% {}'.format(percent, labels.get(obj.id, obj.id)) |
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cv2_im = cv2.rectangle(cv2_im, (x0, y0), (x1, y1), (0, 255, 0), 2) |
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cv2_im = cv2.putText(cv2_im, label, (x0, y0+30), |
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cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 0, 0), 2) |
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cv2_im = cv2.putText(cv2_im, "ALARM !!!!", (10,30), |
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cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255), 2) |
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return cv2_im,True,f'ALARM ! PERSON detected {round(obj.score,1)*100}' |
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return cv2_im,False,"OKAY" |
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def is_time(last_time,threshold): |
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delta=int((datetime.now()-last_time).total_seconds()) |
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logging.debug(delta,last_time,threshold,delta >= threshold) |
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return delta >= threshold |
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if __name__ == '__main__': |
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config = configparser.ConfigParser() |
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configFilePath = '/home/pi/picoral_cctv/cctv.ini' |
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config.read(configFilePath) |
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main() |
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